Identifying high-value leads with predictive analytics

Account-based marketing starts with identifying your most promising leads. Here’s how AI can help you on this critical first step in demand generation.

Let’s assume you have a great product and a good idea of the sort of businesses that it might appeal to. The next step is to identify those accounts. They’re the companies that align closely with your ideal customer profiles (ICPs). The thing is, how do you find them?

Some companies take the shortcut of buying lists of leads. However, not only is this inefficient; it’s also risky. The main problem is that such lists are generalist. At best, they might be tailored to your industry, but not to your specific business model and product. That means you end up wasting time – and potentially harming your reputation – by engaging the wrong prospects.

Account-based marketing (ABM) is a strategic approach, and that means targeting high-value accounts that have been thoroughly vetted. You can do this manually, but it quickly becomes impractical at scale. However, augmenting your prospecting strategy with artificial intelligence (AI) can greatly expand your reach without compromising on lead quality.

In our previous article, we explored the role of intent data in identifying high-value accounts. Here, we’ll explore how predictive analytics can augment that approach.

Understanding predictive analytics

While intent data captures signals indicating which accounts are showing interest in products like your own, predictive analytics helps determine which accounts are most likely to convert based on historical data. For example, platforms like Salesforce Einstein use machine leaning to help marketers score leads based on their likelihood to convert. Combined with intent data, this gives you a full picture of your target market as it stands right now.

What makes predictive analytics so powerful is how it augments intent data by going beyond an account’s firmographic profile to consider things like business performance. As such, it can answer questions like whether the company is growing or reducing its head count or budget, or whether it’s merging with other companies. In other words, while intent data might indicate an interest in buying your product, predictive analytics helps determine how likely that intent is to translate into action.

To get started with predictive analytics, you need to have an ICP (or ICPs) complete with any attributes that are relevant to your business. This might include industry, company revenue, number of employees, location, and pain points. The next step is to apply predictive analytics to these profiles so that you can score and prioritize the accounts based on how closely they resemble them. Once you’ve done that, you’ve set the stage for successful engagement and conversion in your ABM funnel.

Are you ready to level up your sales prospecting? Energize Marketing can help you identify the high-value leads that bring your business the results that matter.